Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations1599
Missing cells0
Missing cells (%)0.0%
Duplicate rows220
Duplicate rows (%)13.8%
Total size in memory150.0 KiB
Average record size in memory96.1 B

Variable types

Numeric12

Alerts

Dataset has 220 (13.8%) duplicate rowsDuplicates
citric acid is highly overall correlated with fixed acidity and 2 other fieldsHigh correlation
density is highly overall correlated with fixed acidityHigh correlation
fixed acidity is highly overall correlated with citric acid and 2 other fieldsHigh correlation
free sulfur dioxide is highly overall correlated with total sulfur dioxideHigh correlation
pH is highly overall correlated with citric acid and 1 other fieldsHigh correlation
total sulfur dioxide is highly overall correlated with free sulfur dioxideHigh correlation
volatile acidity is highly overall correlated with citric acidHigh correlation
citric acid has 132 (8.3%) zeros Zeros

Reproduction

Analysis started2025-04-20 13:36:57.069992
Analysis finished2025-04-20 13:37:29.056650
Duration31.99 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

fixed acidity
Real number (ℝ)

High correlation 

Distinct96
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3196373
Minimum4.6
Maximum15.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:29.211102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile6.1
Q17.1
median7.9
Q39.2
95-th percentile11.8
Maximum15.9
Range11.3
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation1.7410963
Coefficient of variation (CV)0.20927551
Kurtosis1.1321434
Mean8.3196373
Median Absolute Deviation (MAD)1
Skewness0.98275144
Sum13303.1
Variance3.0314164
MonotonicityNot monotonic
2025-04-20T10:37:29.413710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 67
 
4.2%
7.1 57
 
3.6%
7.8 53
 
3.3%
7.5 52
 
3.3%
7 50
 
3.1%
7.7 49
 
3.1%
6.8 46
 
2.9%
7.6 46
 
2.9%
8.2 45
 
2.8%
7.3 44
 
2.8%
Other values (86) 1090
68.2%
ValueCountFrequency (%)
4.6 1
 
0.1%
4.7 1
 
0.1%
4.9 1
 
0.1%
5 6
0.4%
5.1 4
 
0.3%
5.2 6
0.4%
5.3 4
 
0.3%
5.4 5
 
0.3%
5.5 1
 
0.1%
5.6 14
0.9%
ValueCountFrequency (%)
15.9 1
0.1%
15.6 2
0.1%
15.5 2
0.1%
15 2
0.1%
14.3 1
0.1%
14 1
0.1%
13.8 1
0.1%
13.7 2
0.1%
13.5 1
0.1%
13.4 1
0.1%

volatile acidity
Real number (ℝ)

High correlation 

Distinct143
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.52782051
Minimum0.12
Maximum1.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:29.600438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.12
5-th percentile0.27
Q10.39
median0.52
Q30.64
95-th percentile0.84
Maximum1.58
Range1.46
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.1790597
Coefficient of variation (CV)0.33924355
Kurtosis1.2255423
Mean0.52782051
Median Absolute Deviation (MAD)0.12
Skewness0.67159257
Sum843.985
Variance0.032062378
MonotonicityNot monotonic
2025-04-20T10:37:29.806059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 47
 
2.9%
0.5 46
 
2.9%
0.43 43
 
2.7%
0.59 39
 
2.4%
0.58 38
 
2.4%
0.36 38
 
2.4%
0.4 37
 
2.3%
0.49 35
 
2.2%
0.38 35
 
2.2%
0.39 35
 
2.2%
Other values (133) 1206
75.4%
ValueCountFrequency (%)
0.12 3
 
0.2%
0.16 2
 
0.1%
0.18 10
0.6%
0.19 2
 
0.1%
0.2 3
 
0.2%
0.21 6
0.4%
0.22 6
0.4%
0.23 5
 
0.3%
0.24 13
0.8%
0.25 7
0.4%
ValueCountFrequency (%)
1.58 1
 
0.1%
1.33 2
0.1%
1.24 1
 
0.1%
1.185 1
 
0.1%
1.18 1
 
0.1%
1.13 1
 
0.1%
1.115 1
 
0.1%
1.09 1
 
0.1%
1.07 1
 
0.1%
1.04 3
0.2%

citric acid
Real number (ℝ)

High correlation  Zeros 

Distinct80
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27097561
Minimum0
Maximum1
Zeros132
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:30.057148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.09
median0.26
Q30.42
95-th percentile0.6
Maximum1
Range1
Interquartile range (IQR)0.33

Descriptive statistics

Standard deviation0.19480114
Coefficient of variation (CV)0.71888809
Kurtosis-0.78899752
Mean0.27097561
Median Absolute Deviation (MAD)0.17
Skewness0.3183373
Sum433.29
Variance0.037947483
MonotonicityNot monotonic
2025-04-20T10:37:30.264586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 132
 
8.3%
0.49 68
 
4.3%
0.24 51
 
3.2%
0.02 50
 
3.1%
0.26 38
 
2.4%
0.1 35
 
2.2%
0.08 33
 
2.1%
0.21 33
 
2.1%
0.01 33
 
2.1%
0.32 32
 
2.0%
Other values (70) 1094
68.4%
ValueCountFrequency (%)
0 132
8.3%
0.01 33
 
2.1%
0.02 50
 
3.1%
0.03 30
 
1.9%
0.04 29
 
1.8%
0.05 20
 
1.3%
0.06 24
 
1.5%
0.07 22
 
1.4%
0.08 33
 
2.1%
0.09 30
 
1.9%
ValueCountFrequency (%)
1 1
 
0.1%
0.79 1
 
0.1%
0.78 1
 
0.1%
0.76 3
0.2%
0.75 1
 
0.1%
0.74 4
0.3%
0.73 3
0.2%
0.72 1
 
0.1%
0.71 1
 
0.1%
0.7 2
0.1%

residual sugar
Real number (ℝ)

Distinct91
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5388055
Minimum0.9
Maximum15.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:30.466584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile1.59
Q11.9
median2.2
Q32.6
95-th percentile5.1
Maximum15.5
Range14.6
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation1.4099281
Coefficient of variation (CV)0.55535095
Kurtosis28.617595
Mean2.5388055
Median Absolute Deviation (MAD)0.3
Skewness4.5406554
Sum4059.55
Variance1.9878971
MonotonicityNot monotonic
2025-04-20T10:37:30.690664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 156
 
9.8%
2.2 131
 
8.2%
1.8 129
 
8.1%
2.1 128
 
8.0%
1.9 117
 
7.3%
2.3 109
 
6.8%
2.4 86
 
5.4%
2.5 84
 
5.3%
2.6 79
 
4.9%
1.7 76
 
4.8%
Other values (81) 504
31.5%
ValueCountFrequency (%)
0.9 2
 
0.1%
1.2 8
 
0.5%
1.3 5
 
0.3%
1.4 35
 
2.2%
1.5 30
 
1.9%
1.6 58
3.6%
1.65 2
 
0.1%
1.7 76
4.8%
1.75 2
 
0.1%
1.8 129
8.1%
ValueCountFrequency (%)
15.5 1
0.1%
15.4 2
0.1%
13.9 1
0.1%
13.8 2
0.1%
13.4 1
0.1%
12.9 1
0.1%
11 2
0.1%
10.7 1
0.1%
9 1
0.1%
8.9 1
0.1%

chlorides
Real number (ℝ)

Distinct153
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.087466542
Minimum0.012
Maximum0.611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:31.043647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.012
5-th percentile0.054
Q10.07
median0.079
Q30.09
95-th percentile0.1261
Maximum0.611
Range0.599
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.047065302
Coefficient of variation (CV)0.53809492
Kurtosis41.715787
Mean0.087466542
Median Absolute Deviation (MAD)0.01
Skewness5.6803466
Sum139.859
Variance0.0022151427
MonotonicityNot monotonic
2025-04-20T10:37:31.333577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.08 66
 
4.1%
0.074 55
 
3.4%
0.076 51
 
3.2%
0.078 51
 
3.2%
0.084 49
 
3.1%
0.071 47
 
2.9%
0.077 47
 
2.9%
0.082 46
 
2.9%
0.075 45
 
2.8%
0.079 43
 
2.7%
Other values (143) 1099
68.7%
ValueCountFrequency (%)
0.012 2
 
0.1%
0.034 1
 
0.1%
0.038 2
 
0.1%
0.039 4
0.3%
0.041 4
0.3%
0.042 3
0.2%
0.043 1
 
0.1%
0.044 5
0.3%
0.045 4
0.3%
0.046 4
0.3%
ValueCountFrequency (%)
0.611 1
 
0.1%
0.61 1
 
0.1%
0.467 1
 
0.1%
0.464 1
 
0.1%
0.422 1
 
0.1%
0.415 3
0.2%
0.414 2
0.1%
0.413 1
 
0.1%
0.403 1
 
0.1%
0.401 1
 
0.1%

free sulfur dioxide
Real number (ℝ)

High correlation 

Distinct60
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.874922
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:31.705383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q17
median14
Q321
95-th percentile35
Maximum72
Range71
Interquartile range (IQR)14

Descriptive statistics

Standard deviation10.460157
Coefficient of variation (CV)0.65891077
Kurtosis2.023562
Mean15.874922
Median Absolute Deviation (MAD)7
Skewness1.2505673
Sum25384
Variance109.41488
MonotonicityNot monotonic
2025-04-20T10:37:31.985217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 138
 
8.6%
5 104
 
6.5%
10 79
 
4.9%
15 78
 
4.9%
12 75
 
4.7%
7 71
 
4.4%
9 62
 
3.9%
16 61
 
3.8%
17 60
 
3.8%
11 59
 
3.7%
Other values (50) 812
50.8%
ValueCountFrequency (%)
1 3
 
0.2%
2 1
 
0.1%
3 49
 
3.1%
4 41
 
2.6%
5 104
6.5%
5.5 1
 
0.1%
6 138
8.6%
7 71
4.4%
8 56
3.5%
9 62
3.9%
ValueCountFrequency (%)
72 1
 
0.1%
68 2
0.1%
66 1
 
0.1%
57 1
 
0.1%
55 2
0.1%
54 1
 
0.1%
53 1
 
0.1%
52 3
0.2%
51 4
0.3%
50 2
0.1%

total sulfur dioxide
Real number (ℝ)

High correlation 

Distinct144
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.467792
Minimum6
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:32.191026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile11
Q122
median38
Q362
95-th percentile112.1
Maximum289
Range283
Interquartile range (IQR)40

Descriptive statistics

Standard deviation32.895324
Coefficient of variation (CV)0.70791666
Kurtosis3.8098245
Mean46.467792
Median Absolute Deviation (MAD)18
Skewness1.5155313
Sum74302
Variance1082.1024
MonotonicityNot monotonic
2025-04-20T10:37:32.364275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
2.7%
24 36
 
2.3%
18 35
 
2.2%
15 35
 
2.2%
23 34
 
2.1%
14 33
 
2.1%
20 33
 
2.1%
31 32
 
2.0%
38 31
 
1.9%
27 30
 
1.9%
Other values (134) 1257
78.6%
ValueCountFrequency (%)
6 3
 
0.2%
7 4
 
0.3%
8 14
 
0.9%
9 14
 
0.9%
10 27
1.7%
11 26
1.6%
12 29
1.8%
13 28
1.8%
14 33
2.1%
15 35
2.2%
ValueCountFrequency (%)
289 1
0.1%
278 1
0.1%
165 1
0.1%
160 1
0.1%
155 1
0.1%
153 1
0.1%
152 1
0.1%
151 2
0.1%
149 1
0.1%
148 2
0.1%

density
Real number (ℝ)

High correlation 

Distinct436
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.99674668
Minimum0.99007
Maximum1.00369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:32.599356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.99007
5-th percentile0.993598
Q10.9956
median0.99675
Q30.997835
95-th percentile1
Maximum1.00369
Range0.01362
Interquartile range (IQR)0.002235

Descriptive statistics

Standard deviation0.001887334
Coefficient of variation (CV)0.0018934941
Kurtosis0.93407907
Mean0.99674668
Median Absolute Deviation (MAD)0.00113
Skewness0.071287663
Sum1593.7979
Variance3.5620295 × 10-6
MonotonicityNot monotonic
2025-04-20T10:37:32.879186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9972 36
 
2.3%
0.9976 35
 
2.2%
0.9968 35
 
2.2%
0.998 29
 
1.8%
0.9962 28
 
1.8%
0.9978 26
 
1.6%
0.9964 25
 
1.6%
0.997 24
 
1.5%
0.9994 24
 
1.5%
0.9982 23
 
1.4%
Other values (426) 1314
82.2%
ValueCountFrequency (%)
0.99007 2
0.1%
0.9902 1
0.1%
0.99064 2
0.1%
0.9908 1
0.1%
0.99084 1
0.1%
0.9912 1
0.1%
0.9915 1
0.1%
0.99154 1
0.1%
0.99157 1
0.1%
0.9916 2
0.1%
ValueCountFrequency (%)
1.00369 2
0.1%
1.0032 1
 
0.1%
1.00315 3
0.2%
1.00289 1
 
0.1%
1.0026 2
0.1%
1.00242 2
0.1%
1.0022 2
0.1%
1.0021 2
0.1%
1.0018 1
 
0.1%
1.0015 2
0.1%

pH
Real number (ℝ)

High correlation 

Distinct89
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3111132
Minimum2.74
Maximum4.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:33.101002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.74
5-th percentile3.06
Q13.21
median3.31
Q33.4
95-th percentile3.57
Maximum4.01
Range1.27
Interquartile range (IQR)0.19

Descriptive statistics

Standard deviation0.15438646
Coefficient of variation (CV)0.046626755
Kurtosis0.80694251
Mean3.3111132
Median Absolute Deviation (MAD)0.1
Skewness0.1936835
Sum5294.47
Variance0.023835181
MonotonicityNot monotonic
2025-04-20T10:37:33.314785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 57
 
3.6%
3.36 56
 
3.5%
3.26 53
 
3.3%
3.39 48
 
3.0%
3.38 48
 
3.0%
3.29 46
 
2.9%
3.32 45
 
2.8%
3.34 43
 
2.7%
3.28 42
 
2.6%
3.22 39
 
2.4%
Other values (79) 1122
70.2%
ValueCountFrequency (%)
2.74 1
 
0.1%
2.86 1
 
0.1%
2.87 1
 
0.1%
2.88 2
0.1%
2.89 4
0.3%
2.9 1
 
0.1%
2.92 4
0.3%
2.93 3
0.2%
2.94 4
0.3%
2.95 1
 
0.1%
ValueCountFrequency (%)
4.01 2
0.1%
3.9 2
0.1%
3.85 1
 
0.1%
3.78 2
0.1%
3.75 1
 
0.1%
3.74 1
 
0.1%
3.72 3
0.2%
3.71 4
0.3%
3.7 1
 
0.1%
3.69 4
0.3%

sulphates
Real number (ℝ)

Distinct96
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.65814884
Minimum0.33
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:33.538066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.33
5-th percentile0.47
Q10.55
median0.62
Q30.73
95-th percentile0.93
Maximum2
Range1.67
Interquartile range (IQR)0.18

Descriptive statistics

Standard deviation0.16950698
Coefficient of variation (CV)0.25755113
Kurtosis11.720251
Mean0.65814884
Median Absolute Deviation (MAD)0.08
Skewness2.4286724
Sum1052.38
Variance0.028732616
MonotonicityNot monotonic
2025-04-20T10:37:33.786246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 69
 
4.3%
0.58 68
 
4.3%
0.54 68
 
4.3%
0.62 61
 
3.8%
0.56 60
 
3.8%
0.57 55
 
3.4%
0.59 51
 
3.2%
0.53 51
 
3.2%
0.55 50
 
3.1%
0.63 48
 
3.0%
Other values (86) 1018
63.7%
ValueCountFrequency (%)
0.33 1
 
0.1%
0.37 2
 
0.1%
0.39 6
 
0.4%
0.4 4
 
0.3%
0.42 5
 
0.3%
0.43 8
0.5%
0.44 16
1.0%
0.45 12
0.8%
0.46 18
1.1%
0.47 19
1.2%
ValueCountFrequency (%)
2 1
 
0.1%
1.98 1
 
0.1%
1.95 2
0.1%
1.62 1
 
0.1%
1.61 1
 
0.1%
1.59 1
 
0.1%
1.56 1
 
0.1%
1.36 3
0.2%
1.34 1
 
0.1%
1.33 1
 
0.1%

alcohol
Real number (ℝ)

Distinct65
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.422983
Minimum8.4
Maximum14.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:33.994780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum8.4
5-th percentile9.2
Q19.5
median10.2
Q311.1
95-th percentile12.5
Maximum14.9
Range6.5
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.0656676
Coefficient of variation (CV)0.10224209
Kurtosis0.20002931
Mean10.422983
Median Absolute Deviation (MAD)0.7
Skewness0.86082881
Sum16666.35
Variance1.1356474
MonotonicityNot monotonic
2025-04-20T10:37:34.216293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.5 139
 
8.7%
9.4 103
 
6.4%
9.8 78
 
4.9%
9.2 72
 
4.5%
10 67
 
4.2%
10.5 67
 
4.2%
9.3 59
 
3.7%
9.6 59
 
3.7%
11 59
 
3.7%
9.7 54
 
3.4%
Other values (55) 842
52.7%
ValueCountFrequency (%)
8.4 2
 
0.1%
8.5 1
 
0.1%
8.7 2
 
0.1%
8.8 2
 
0.1%
9 30
1.9%
9.05 1
 
0.1%
9.1 23
 
1.4%
9.2 72
4.5%
9.233333333 1
 
0.1%
9.25 1
 
0.1%
ValueCountFrequency (%)
14.9 1
 
0.1%
14 7
0.4%
13.6 4
0.3%
13.56666667 1
 
0.1%
13.5 1
 
0.1%
13.4 3
0.2%
13.3 3
0.2%
13.2 1
 
0.1%
13.1 2
 
0.1%
13 6
0.4%

quality
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6360225
Minimum3
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.6 KiB
2025-04-20T10:37:34.389225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5
Q15
median6
Q36
95-th percentile7
Maximum8
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.80756944
Coefficient of variation (CV)0.14328712
Kurtosis0.29670812
Mean5.6360225
Median Absolute Deviation (MAD)1
Skewness0.21780158
Sum9012
Variance0.6521684
MonotonicityNot monotonic
2025-04-20T10:37:34.539905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 681
42.6%
6 638
39.9%
7 199
 
12.4%
4 53
 
3.3%
8 18
 
1.1%
3 10
 
0.6%
ValueCountFrequency (%)
3 10
 
0.6%
4 53
 
3.3%
5 681
42.6%
6 638
39.9%
7 199
 
12.4%
8 18
 
1.1%
ValueCountFrequency (%)
8 18
 
1.1%
7 199
 
12.4%
6 638
39.9%
5 681
42.6%
4 53
 
3.3%
3 10
 
0.6%

Interactions

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2025-04-20T10:37:18.147870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-20T10:37:21.096437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-20T10:37:24.069821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-20T10:37:26.391743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-20T10:37:34.674605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
alcoholchloridescitric aciddensityfixed acidityfree sulfur dioxidepHqualityresidual sugarsulphatestotal sulfur dioxidevolatile acidity
alcohol1.000-0.2850.096-0.462-0.067-0.0810.1800.4790.1170.207-0.258-0.225
chlorides-0.2851.0000.1130.4110.2510.001-0.234-0.1900.2130.0210.1300.159
citric acid0.0960.1131.0000.3520.662-0.076-0.5480.2130.1760.3310.009-0.610
density-0.4620.4110.3521.0000.623-0.041-0.312-0.1770.4220.1610.1290.025
fixed acidity-0.0670.2510.6620.6231.000-0.175-0.7070.1140.2210.213-0.088-0.278
free sulfur dioxide-0.0810.001-0.076-0.041-0.1751.0000.116-0.0570.0750.0460.7900.021
pH0.180-0.234-0.548-0.312-0.7070.1161.000-0.044-0.090-0.080-0.0100.234
quality0.479-0.1900.213-0.1770.114-0.057-0.0441.0000.0320.377-0.197-0.381
residual sugar0.1170.2130.1760.4220.2210.075-0.0900.0321.0000.0380.1450.032
sulphates0.2070.0210.3310.1610.2130.046-0.0800.3770.0381.000-0.001-0.326
total sulfur dioxide-0.2580.1300.0090.129-0.0880.790-0.010-0.1970.145-0.0011.0000.094
volatile acidity-0.2250.159-0.6100.025-0.2780.0210.234-0.3810.032-0.3260.0941.000

Missing values

2025-04-20T10:37:28.754203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-20T10:37:28.953593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
07.40.700.001.90.07611.034.00.99783.510.569.45
17.80.880.002.60.09825.067.00.99683.200.689.85
27.80.760.042.30.09215.054.00.99703.260.659.85
311.20.280.561.90.07517.060.00.99803.160.589.86
47.40.700.001.90.07611.034.00.99783.510.569.45
57.40.660.001.80.07513.040.00.99783.510.569.45
67.90.600.061.60.06915.059.00.99643.300.469.45
77.30.650.001.20.06515.021.00.99463.390.4710.07
87.80.580.022.00.0739.018.00.99683.360.579.57
97.50.500.366.10.07117.0102.00.99783.350.8010.55
fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality
15896.60.7250.207.80.07329.079.00.997703.290.549.25
15906.30.5500.151.80.07726.035.00.993143.320.8211.66
15915.40.7400.091.70.08916.026.00.994023.670.5611.66
15926.30.5100.132.30.07629.040.00.995743.420.7511.06
15936.80.6200.081.90.06828.038.00.996513.420.829.56
15946.20.6000.082.00.09032.044.00.994903.450.5810.55
15955.90.5500.102.20.06239.051.00.995123.520.7611.26
15966.30.5100.132.30.07629.040.00.995743.420.7511.06
15975.90.6450.122.00.07532.044.00.995473.570.7110.25
15986.00.3100.473.60.06718.042.00.995493.390.6611.06

Duplicate rows

Most frequently occurring

fixed acidityvolatile aciditycitric acidresidual sugarchloridesfree sulfur dioxidetotal sulfur dioxidedensitypHsulphatesalcoholquality# duplicates
226.70.4600.241.70.07718.034.00.994803.390.6010.664
527.20.3600.462.10.07424.044.00.995343.400.8511.074
637.20.6950.132.00.07612.020.00.995463.290.5410.154
817.50.5100.021.70.08413.031.00.995383.360.5410.564
56.00.5000.001.40.05715.026.00.994483.360.459.553
126.40.6400.211.80.08114.031.00.996893.590.669.853
397.00.6500.022.10.0668.025.00.997203.470.679.563
407.00.6900.072.50.09115.021.00.995723.380.6011.363
607.20.6300.001.90.09714.038.00.996753.370.589.063
1047.80.6000.262.00.08031.0131.00.996223.210.529.953